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Normal Distribution For Beginners with Python | Python Tutorial | Machine Learning |
How to Plot Normal Distribution in Python - Python Statistics Tutorial
In this chapter we will learn how to create an array where the values are concentrated around a given value.

In probability theory this kind of data distribution is known as the normal data distribution, or the Gaussian data distribution, after the mathematician Carl Friedrich Gauss who came up with the formula of this data distribution.

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Transcript

0:10
[Music]
0:19
normal data distribution
0:22
in this chapter we will learn how to
0:23
create an array where the values are
0:25
concentrated around a given value
0:28
in probability theory this kind of data
0:30
is also known as the normal data
0:32
distribution or the gaussian data
0:34
distribution after the mathematician
0:36
carl friedrich gause who came up with
0:38
the formula of this data distribution
0:41
for example
0:43
import the following python libraries
0:46
one numpy as np
0:49
two
0:50
matplotlib.pyplot as plt
0:53
then method shown below
0:55
in the above method we use the array
0:57
from the
0:58
numpy.random.normal method with 100 000
1:01
values to draw a histogram with 100 bars
1:05
then we specify that the mean value is
1:07
5.0 and the standard deviation is 1.0
1:12
meaning that the value should be
1:13
concentrated around 5.0 and rarely
1:16
further away than 1.0 from the mean
1:19
and as you can see from the histogram
1:21
most values are between 4.0 and 6.0 with
1:24
a top at approximately 5.0
1:28
thank you for watching this video kindly
1:30
like subscribe and turn on your
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notification for more videos see you
1:34
next time and bye bye
1:46
[Music]
1:50
you
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